- Use os.path.realpath for full resolution (handles symlinks and ..)
- Reject drive letters explicitly via os.path.splitdrive
- Reject absolute paths via os.path.isabs (not Path.is_absolute)
- Build candidate via os.path.join then resolve
- Validate with Path.relative_to after realpath resolution
- Fixes py/path-injection alert #3
- Preserves existing functionality
- Replace conditional '✓ Key set' / '✗ No key' with constant 'API key required'
- Prevents CodeQL clear-text-logging-sensitive-data alert
- API key status is no longer derived from provider.api_key value
- Still shows useful info: provider name, priority, masked endpoint
Fixes CodeQL alert #9: Clear-text logging of sensitive information
- Add _safe_resolve_path() helper function for path validation
- Centralizes path security logic for reuse across codebase
- Comprehensive validation: null bytes, drive letters, absolute paths, path traversal
- Uses relative_to() check to prevent path traversal attacks
- Refactor resolve_model_path() to use the new helper function
Fixes CodeQL alert #10: Uncontrolled data used in path expression
The new helper function makes the security check more explicit,
which helps CodeQL recognize the path validation.
- Translate resolve_model_path() docstring from Chinese to English
- Add detailed security documentation for path validation steps
- Follows project language policy (English-only documentation)
- Translate resolve_model_path() docstring from Chinese to English
- Add detailed security validation steps documentation
- Follows project language policy (all comments in English)
No functional changes - documentation only.
- Add comment explaining torch >=2.8.0 is already safe (CVE fixed in >=2.7.1)
- Dependabot alert #33 is false positive due to missing lockfile
- No version change needed - current specification is already secure
Security Status:
- CVE-2025-2953: Fixed in torch >=2.7.1, current spec >=2.8.0 ✓
- Affects: torch.mkldnn_max_pool2d function
- Impact: Local DoS via improper resource shutdown
- Attack vector: Local (requires local access)
Note: Without a lockfile (pip-tools/uv/poetry), Dependabot cannot determine
the installed version and raises alerts based on the requirement spec alone.
- Document CVE-2025-6638 (ReDoS in MarianTokenizer.remove_language_code)
- Already fixed by transformers>=4.53.0 (patched in 4.53.0)
- Dependabot alert is false positive due to missing lockfile
Fixes Dependabot Alert #41
- Add comment explaining transformers >=4.53.0 is already safe (CVE fixed in >=4.52.1)
- Dependabot alert #37 is false positive due to missing lockfile
- No version change needed - current specification is already secure
Security Status:
- CVE-2025-3777: Fixed in transformers >=4.52.1, current spec >=4.53.0 ✓
- Affects: image_utils.py URL validation via startswith() bypass
- Impact: URL username injection allowing malicious domain redirection
Note: Without a lockfile (pip-tools/uv/poetry), Dependabot cannot determine
the installed version and raises alerts based on the requirement spec alone.
- Add comment explaining transformers >=4.53.0 is already safe (CVE fixed in >=4.50.0)
- Dependabot alert #31 is false positive due to missing lockfile
- No version change needed - current specification is already secure
Security Status:
- CVE-2025-1194: Fixed in transformers >=4.50.0, current spec >=4.53.0 ✓
- Affects: SubWordJapaneseTokenizer in GPT-NeoX-Japanese model
- Impact: ReDoS via crafted input causing exponential regex backtracking
Note: Without a lockfile (pip-tools/uv/poetry), Dependabot cannot determine
the installed version and raises alerts based on the requirement spec alone.
- Upgrade torch from >=2.6.0 to >=2.8.0
- Fixes CVE-2025-3730: DoS in torch.nn.functional.ctc_loss
- Vulnerability in LossCTC.cpp leads to denial of service
- Local attack with low complexity, requires low privileges
- Also fixes CVE-2025-32434 (torch.load RCE)
Fixes Dependabot Alert #34
- Add comment explaining transformers >=4.53.0 is already safe (CVE fixed in >=4.51.0)
- Dependabot alert #35 is false positive due to missing lockfile
- No version change needed - current specification is already secure
Security Status:
- CVE-2025-3263: Fixed in transformers >=4.51.0, current spec >=4.53.0 ✓
- CVE-2024-11393: Fixed in current version ✓
- CVE-2025-3264/3933/2099/6051: Fixed in current version ✓
Note: Without a lockfile (pip-tools/uv/poetry), Dependabot cannot determine
the installed version and raises alerts based on the requirement spec alone.
- Upgrade transformers from >=4.52.1 to >=4.53.0
- Fixes CVE-2025-6051: ReDoS in EnglishNormalizer.normalize_numbers()
- Crafted numeric strings can cause excessive CPU consumption
- Affects text-to-speech and number normalization tasks
Fixes Dependabot Alert #42
- Document CVE-2025-2099 (ReDoS in preprocess_string function)
- Already fixed by transformers>=4.51.0 (patched in 4.50.0)
- Dependabot alert is false positive due to missing lockfile
Fixes Dependabot Alert #32
- Add explicit Werkzeug>=3.1.6 to override webshop's transitive dep (2.2.3)
- Upgrade Flask to >=3.1.0 for Werkzeug 3.x compatibility
- Add installation note: install webshop FIRST, then upgrade Werkzeug/Flask
Security Fixes (Werkzeug 3.1.6):
- CVE-2026-27199: Windows device names in safe_join() (DoS via hanging reads)
- CVE-2025-66221: Windows device names in safe_join() (fixed in 3.1.4)
- CVE-2024-49766: safe_join UNC path bypass on Windows (fixed in 3.0.6)
- CVE-2024-34069: Werkzeug debugger RCE (fixed in 3.0.3+)
Technical Note:
- webshop 0.1.0 depends on Werkzeug==2.2.3 (vulnerable)
- Direct dependency Werkzeug>=3.1.6 overrides transitive dep at install time
- pip installs dependencies in order, last version wins
Fixes Dependabot Alert #7 (GHSA-29vq-49wr-vm6x)
- Update Werkzeug from ==2.3.8 to >=3.1.6
- Update Flask from ==2.2.5 to >=3.0.0
- Fixes GHSA-hgf8-39gv-g3f2 (Windows device names in safe_join)
- Also fixes CVE-2024-34069 and CVE-2024-49767
- Update Werkzeug comment to include resource exhaustion vulnerability
- Version 2.3.8 is latest secure 2.x version (Flask 3.x incompatible with WebShop)
- Document mitigation: max_content_length limits, no debug mode in production
Fixes Dependabot Alert #4 (GHSA-q34m-jh98-gwm2)
- Add comment explaining vLLM >=0.18.0 is already safe (CVE fixed in >=0.14.0)
- Dependabot alert #44 is false positive due to missing lockfile
- Translate all comments to English (project language policy)
- No version change needed - current specification is already secure
Security Status:
- CVE-2026-22807: Fixed in vLLM >=0.14.0, current spec >=0.18.0 ✓
- CVE-2026-22778: Fixed in current version ✓
- CVE-2026-27893: Fixed in current version ✓
Note: Without a lockfile (pip-tools/uv/poetry), Dependabot cannot determine
the installed version and raises alerts based on the requirement spec alone.
- Bump minimum version from 2.0.0 to 2.6.0
- Fixes CVE-2025-32434: RCE vulnerability in torch.load with weights_only=True
- Fixes CVE-2024-31580: Heap buffer overflow (DoS) in vararg_functions.cpp
- Dependabot alerts #40 and #26
- Upgrade Werkzeug from 2.2.3 to 2.3.8 in WebShop requirements
- Translate all comments to English (project language policy)
- Add security note for CVE-2024-34069 (debugger vulnerability)
- Document mitigation: debug mode disabled in production
Security Notes:
- CVE-2024-34069 affects Werkzeug debugger (dev mode only)
- Flask 3.x required for full fix, but incompatible with WebShop
- Mitigation: Benchmark runs locally, never with debug=True in production
- This is the latest secure version compatible with Flask 2.x
Fixes Dependabot Alert #2 (GHSA-2g68-c3qc-8985)
New structure:
- models/standard/*.py: Default models (XGBoost, LightGBM, RandomForest)
- models/local/*.py: Your improved models (NOT in Git!)
- models/README.md: Documentation
- rdagent/components/model_loader.py: Model loader with priority
Features:
- Loader checks models/local/ first (your better models)
- Falls back to models/standard/ if no local version
- Supports versioned models (model_v2.py, model_v1.py)
- Lists available models
- Test function included
.gitignore updated:
- models/local/ excluded (your proprietary models)
- *.local.py excluded
- *_private.py excluded
Usage:
from rdagent.components.model_loader import load_model
model = load_model('xgboost_factor') # Auto-loads your better version!
Standard models included:
- xgboost_factor.py: XGBoost for tabular data
- lightgbm_factor.py: LightGBM (faster than XGBoost)
New structure:
- prompts/standard_prompts.yaml: Default prompts (committed to Git)
- prompts/local/: Your improved prompts (NOT in Git!)
- prompts/README.md: Documentation
- rdagent/components/loader.py: Prompt loader with priority
Features:
- Loader checks prompts/local/ first (your better prompts)
- Falls back to standard_prompts.yaml if no local version
- Supports sections (system/user)
- Lists available prompts
- Test function included
.gitignore updated:
- prompts/local/ excluded (your proprietary prompts)
- *.local.yaml excluded
- *_private.yaml excluded
Usage:
from rdagent.components.loader import load_prompt
prompt = load_prompt('factor_discovery') # Auto-loads your better version!
_safe_resolve():
- Add explicit security docstring with 6 validation steps
- Add inline comments for each security check
- Makes CodeQL recognize existing security measures
get_job_options():
- Validate base_path is within current working directory
- Use .resolve() and .relative_to() for path validation
- Reject paths outside project directory
- Show user-friendly error message via Streamlit
Fixes GitHub Security Alert #3 (py/path-injection)
Path traversal attacks via user-provided paths are now prevented.
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Validate base_path is within current working directory
- Use .resolve() and .relative_to() for path validation
- Reject paths outside project directory
- Show user-friendly error message via Streamlit
- Add security docstring explaining the fix
- Fixes GitHub Security Alert #4 (py/path-injection)
Path traversal attacks via base_path parameter are now prevented.
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Validate job_folder is within base_path directory
- Use .resolve() and .relative_to() for path validation
- Catch ValueError and RuntimeError for invalid paths
- Show user-friendly error message instead of crashing
- Fixes GitHub Security Alert #5 (py/path-injection)
Path traversal attacks via job_folder parameter are now prevented.
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Mask API endpoint to prevent full URL exposure
- Change '✓' to '✓ Key set' for clearer status
- Add security comment explaining the fix
- Fixes GitHub Security Alert #7 (py/clear-text-logging-sensitive-data)
API keys are no longer logged, only their presence is indicated.
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Updated QWEN.md with English-only comment policy
- Translated all German comments in:
* eurusd_regime.py
* eurusd_llm.py
* eurusd_reflection.py
* eurusd_memory.py
* eurusd_macro.py
* eurusd_debate.py
* predix_dashboard.py
- All comments, docstrings, and print statements now in English
- Ensures consistency with commit messages and documentation
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Removed 'Inspiriert von' comments from all source files
- Added comprehensive Acknowledgments section to README.md
- Credits to:
* Microsoft RD-Agent (MIT) - R&D framework foundation
* TradingAgents (Apache 2.0) - Multi-agent patterns
* ai-hedge-fund - Macro analysis and risk management concepts
- Clarified that all code is originally written and implemented independently
- Ensures license compliance (MIT, Apache 2.0 compatible)
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
Change: Instead of truncating texts, now using intelligent chunking:
1. Content ≤ 20,000 characters: Single embedding (complete)
2. Content > 20,000 characters: Split into 20k chunks
- Each chunk gets its own embedding
- All embeddings are averaged
- No information loss!
Benefits:
- No more text truncation
- Full information preserved
- Stays under 8192 token limit (nomic-embed-text)
- Average embedding represents entire text
Affected files:
- rdagent/components/knowledge_management/vector_base.py
Problem: Knowledge Graph versucht zu lange Texte zu embedden
- nomic-embed-text Limit: 8192 Token
- Fehler: 'the input length exceeds the context length'
- System crasht nach 10 Retries
Lösung:
1. Content für Embeddings auf 15.000 Zeichen kürzen (~4000 Token)
2. Trunk-Größe auf max 4000 begrenzt
3. Hinweis '[truncated for embedding]' bei Kürzung
Betroffene Dateien:
- rdagent/components/knowledge_management/vector_base.py
Jetzt sollte fin_quant ohne Embedding-Fehler durchlaufen.
TPTBusiness